leonfoks
Got my PhD in Geophysics at the Colorado School of Mines. Currently working on massively parallel Bayesian inference for electro-magnetic data.
Contractor U.S. Geological SurveyDenver, CO
Pinned Repositories
cdi_dl_workshop
A collection of jupyter notebooks for image classification and recognition using deep transfer learning
cmake_fortran
My cmake files i've had to write for Fortran. It's not pretty, but it's gotten my jobs done.
coretran
An easy to follow library to make Fortran easier in general with wrapped interfaces, sorting routines, kD-Trees, and other algorithms to handle scientific data and concepts. The library contains core fortran routines and object-oriented classes.
discretize
Discretization tools for finite volume and inverse problems.
dl_tools
A collection of tools for image classification and recognition using deep transfer learning
fgsl
Fortran interface to the GNU Scientific Library
landslides-trigrs
oo_hdf5_fortran
Object-oriented, clean, simple HDF5 modern Fortran 2018 interface
physical_properties
A class that provides physical property labels and units
SciFortran
A library of fortran modules and routines for scientific calculations (*in a way* just like scipy for python)
leonfoks's Repositories
leonfoks/coretran
An easy to follow library to make Fortran easier in general with wrapped interfaces, sorting routines, kD-Trees, and other algorithms to handle scientific data and concepts. The library contains core fortran routines and object-oriented classes.
leonfoks/cmake_fortran
My cmake files i've had to write for Fortran. It's not pretty, but it's gotten my jobs done.
leonfoks/landslides-trigrs
leonfoks/physical_properties
A class that provides physical property labels and units
leonfoks/discretize
Discretization tools for finite volume and inverse problems.
leonfoks/empymod
An open-source full 3D electromagnetic modeller for 1D VTI media in Python.
leonfoks/ga-aem
Modelling and Inversion of Airborne Electromagnetic (AEM) Data in 1D
leonfoks/geocube
Tool to convert geopandas vector data into rasterized xarray data.
leonfoks/geopandas
Python tools for geographic data
leonfoks/gmt-python
A Python interface for the Generic Mapping Tools
leonfoks/h5netcdf
Pythonic interface to netCDF4 via h5py
leonfoks/h5xarray
leonfoks/lava2d
leonfoks/Lemma
Lemma is an ElectroMagnetic Modelling API
leonfoks/lmfit-py
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize.leastsq, and with many additional classes and methods for curve fitting
leonfoks/mix_T
Package for modeling data using finite or infinite mixtures of multivariate Student's t-distributions
leonfoks/mpi4py_utilities
leonfoks/mpigeopandas
leonfoks/mpixarray
leonfoks/numba-dynamic-array
dynamically changing shape arrays.
leonfoks/pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
leonfoks/pest-gw-utils-linux
This repository is adds a bash script to compile the PEST groundwater utilities (See J. Doherty main page: http://www.pesthomepage.org/)
leonfoks/pyhmsa
Python implementation of the MSA / MAS / AMAS Hyper-Dimensional Data File specification
leonfoks/pysurf96
Python wrapper for modelling surface wave dispersion curves from surf96 - Computer Programs in Seismology, R. Hermann
leonfoks/rioxarray
geospatial xarray extension powered by rasterio
leonfoks/StatArray
Extension to Numpy that allows the attachment of statistical distributions to evaluate priors, propose new values and store posterior distributions
leonfoks/stdlib
Fortran Standard Library
leonfoks/swb2
SWB 2.0: a refactored version of the Soil-Water-Balance code
leonfoks/t-Student-Mixture-Models
Implementation of the paper: 'Robust mixture modelling using the t distribution', D. Peel and G. J. McLachlan.
leonfoks/xstrm
A USGS preliminary/provisional software package and associated command line tool that captures universal methods for stream network summarization. This work builds on original concepts from Tsang, Yin-Phan, Daniel Wieferich, Kuolin Fung, Dana M. Infante, and Arthur R. Cooper. 2014. An approach for aggregating upstream catchment information to support research and management of fluvial systems across large landscapes. SpringerPlus, vol. 3, no. 589. https://doi.org/10.1186/2193-1801-3-589.